States and parameters estimation in induction motor using Bayesian techniques

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper addresses the problem of rotor speed, flux and parameters estimation of induction motor on the basis of a three-order electrical model. Thus, we propose to use a particle filtering (PF) to estimate states and parameters for an induction motor. It is assumed that only the voltages stator currents are measurable. In addition, the rotor resistance and magnetizing inductance, which vary with the motor temperature and magnetization level, can also be estimated within the same framework. Hence, the objective of this work is to estimate three states (the rotor speed, the rotor flux, and the stator flux) and two parameters (the rotor resistance and the magnetizing inductance). Simulation analysis demonstrates that the Bayesian algorithm can well estimate the states/parameters under disturbs of the noise, and it provides efficient accuracies for the states estimation. In addition, detailed case studies show that Bayesian algorithm has advantages over Unscented Kalman filter (UKF) for highly nonlinear estimation problems. Evaluation of the methods was performed by using Root Mean Square Error.

Original languageEnglish
Title of host publication2013 10th International Multi-Conference on Systems, Signals and Devices, SSD 2013
DOIs
Publication statusPublished - 2013
Event2013 10th International Multi-Conference on Systems, Signals and Devices, SSD 2013 - Hammamet, Tunisia
Duration: 18 Mar 201321 Mar 2013

Other

Other2013 10th International Multi-Conference on Systems, Signals and Devices, SSD 2013
CountryTunisia
CityHammamet
Period18/3/1321/3/13

Fingerprint

State estimation
Induction motors
Parameter estimation
Rotors
Fluxes
Inductance
Stators
Kalman filters
Mean square error
Magnetization
Electric potential
Temperature

Keywords

  • Bayesian approach
  • induction motor
  • States/parameters estimation

ASJC Scopus subject areas

  • Signal Processing

Cite this

Mansouri, M., Mohamed-Seghir, M., Nounou, H., Nounou, M., & Abu-Rub, H. (2013). States and parameters estimation in induction motor using Bayesian techniques. In 2013 10th International Multi-Conference on Systems, Signals and Devices, SSD 2013 [6564046] https://doi.org/10.1109/SSD.2013.6564046

States and parameters estimation in induction motor using Bayesian techniques. / Mansouri, Majdi; Mohamed-Seghir, Mostefa; Nounou, Hazem; Nounou, Mohamed; Abu-Rub, Haitham.

2013 10th International Multi-Conference on Systems, Signals and Devices, SSD 2013. 2013. 6564046.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mansouri, M, Mohamed-Seghir, M, Nounou, H, Nounou, M & Abu-Rub, H 2013, States and parameters estimation in induction motor using Bayesian techniques. in 2013 10th International Multi-Conference on Systems, Signals and Devices, SSD 2013., 6564046, 2013 10th International Multi-Conference on Systems, Signals and Devices, SSD 2013, Hammamet, Tunisia, 18/3/13. https://doi.org/10.1109/SSD.2013.6564046
Mansouri M, Mohamed-Seghir M, Nounou H, Nounou M, Abu-Rub H. States and parameters estimation in induction motor using Bayesian techniques. In 2013 10th International Multi-Conference on Systems, Signals and Devices, SSD 2013. 2013. 6564046 https://doi.org/10.1109/SSD.2013.6564046
Mansouri, Majdi ; Mohamed-Seghir, Mostefa ; Nounou, Hazem ; Nounou, Mohamed ; Abu-Rub, Haitham. / States and parameters estimation in induction motor using Bayesian techniques. 2013 10th International Multi-Conference on Systems, Signals and Devices, SSD 2013. 2013.
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